{"as_of":"2026-08-10T22:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66aadc78d01e7189f594c2eaaedb70ccc943240e7a4a97d70001668b4a5af575","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:46:51.240094Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T12:41:25.587050Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.05390","last_updated":"2023-12-08T22:04:53Z","snapshot_observed_at":"2026-08-08T23:25:48.233092Z","submitted_at":"2023-12-08T22:04:53Z","title":"NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.05390","snapshot_observed_at":"2026-08-10T22:46:51.240094Z","title":"Noiseclr: A contrastive learning approach for unsupervised discovery of interpretable directions in diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.00873","last_updated":"2025-01-01T15:35:14Z","snapshot_observed_at":"2026-08-10T22:38:22.191989Z","submitted_at":"2025-01-01T15:35:14Z","title":"Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T22:46:51.240094Z"},"links":{"cited_paper":"/paper/2312.05390","citing_paper":"/paper/2501.00873"},"observation_digest":"sha256:454b00cac8830f759bbb55356e04f37a5617d357aaa6dc8da915ba866cbdf64f","observation_id":"edede7f6-1f6b-45f3-a65f-7ced05952d99","resolution":{"observed_at":"2026-08-10T22:46:51.240094Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.05390","last_updated":"2023-12-08T22:04:53Z","snapshot_observed_at":"2026-08-08T23:25:48.233092Z","submitted_at":"2023-12-08T22:04:53Z","title":"NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models","version":1},"cited_work":{"arxiv_id":"2312.05390","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.05390","snapshot_observed_at":"2026-08-07T12:41:25.587050Z","title":"NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models","venue":"cs.CV","work_id":"ea7de911-a477-4958-a8be-9f7a81b472e7","year":2023},"citing_paper":{"arxiv_id":"2505.23758","last_updated":"2025-05-29T17:59:46Z","snapshot_observed_at":"2026-08-10T11:55:32.445896Z","submitted_at":"2025-05-29T17:59:46Z","title":"LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:41:20.492965Z"},"links":{"cited_paper":"/paper/2312.05390","citing_paper":"/paper/2505.23758"},"observation_digest":"sha256:606de3dc20b4354cf1ecdf0bd77017ca122a4b76fe1337d95c52106dba23a58c","observation_id":"128036f1-c5fc-4676-be17-26793af5b0ab","resolution":{"observed_at":"2026-08-07T12:41:25.627527Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.05390/citation-record","integrity":"/paper/2312.05390/integrity","json":"/paper/2312.05390/citation-record.json","paper":"/paper/2312.05390"},"outbound":[],"paper":{"arxiv_id":"2312.05390","last_updated":"2023-12-08T22:04:53Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T23:25:48.233092Z","submitted_at":"2023-12-08T22:04:53Z","title":"NoiseCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions in Diffusion Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.05390."}